BrainChip Holdings Ltd, based in Laguna Hills, California, launched the Akida Pico on October 1, 2024, introducing a low-power acceleration co-processor designed for compact, ultra-low power portable devices.

The Akida Pico targets a wide range of applications, including consumer electronics, healthcare, IoT, defense, and voice activation, making it versatile for various industries.

This co-processor is capable of executing specific neural network models with a power consumption of less than one milliwatt, making it particularly suitable for battery-operated devices.

Built on the Akida2 event-based computing platform, the Akida Pico operates efficiently under 1 milliwatt, enhancing its suitability for continuous monitoring systems.

The chip offers secure personalization features for applications such as voice wake detection, keyword spotting, and audio enhancement, enhancing user interaction.

Designed to wake up microcontrollers while minimizing power consumption, the processor filters out false alarms until an event is detected, contributing to energy savings.

BrainChip claims substantial power savings with the Akida Pico, potentially reducing energy consumption significantly compared to traditional models.

Key benefits of the Akida Pico include an ultra-low power neural processing unit (NPU) core, minimal standby power consumption, and a compact logic die area, optimizing it for energy efficiency.

CEO Sean Hehir emphasized that the Akida Pico is designed for users with varying levels of AI expertise, facilitating the creation of efficient neural networks.

The Akida platform is particularly ideal for low-latency applications, including robotics, drones, and automotive technologies, supporting early detection and responsiveness.

BrainChip's MetaTF software allows developers to optimize Temporal-Enabled Neural Networks (TENNs) for the Akida Pico using familiar frameworks like TensorFlow/Keras and Pytorch.

Despite the promising features, neuromorphic computing, including the Akida Pico, has yet to find widespread commercial applications, raising concerns about the capabilities of low-power AI solutions.